Contents
Can we use CNN for speech recognition?
CNN is used to perform the feature learning and classification, and CRFs are used for the decoding stage. The results on TIMIT phone recognition task also confirm that the system effectively learns the features from raw speech and performs better than traditional systems that take cepstral features as input [36].
What does convolutional neural network do?
A Convolutional Neural Network (ConvNet/CNN) is a Deep Learning algorithm which can take in an input image, assign importance (learnable weights and biases) to various aspects/objects in the image and be able to differentiate one from the other.
Is speech recognition part of NLP?
NLP works closely with speech/voice recognition and text recognition engines. NLP refers to the evolving set of computer and AI-based technologies that allow computers to learn, understand, and produce content in human languages. The technology works closely with speech/voice recognition and text recognition engines.
How is semi-CNN used in speech recognition?
The candidate features, in the second step, are used as the input to semi-CNN to learn affect-salient, discriminative features using a novel objective function that encourages the feature saliency, orthogonality and discrimination.
How does data augmentation for speech recognition improve training speed?
Given a spectrogram, you can view it as an image where x axis is time while y axis is frequency. Intuitively, it improves training speed because no data transformation between waveform data to spectrogram data but augmenting spectrogram data.
How does the accuracy of speech recognition depend?
Furthermore, the accuracy of speech recognition does not only rely on the efficiency of a model, but also of a speech feature selection [12].
Which is the best GPU for speech recognition?
For the .wav files, I used a subset of training data from the Kaggle competition- Tensorflow Speech Recognition Challenge. Google Colaboratory is used for training. It provides free GPU usage for 12 hours. It is not very fast but quite good for this project. Audio files are sampled at 16000 sampling rate.